Insurers Are Leveraging More Third-Party Data Than Ever from Wide Range of Providers

Data is a powerful and valuable asset for any insurer, and the industry has a long history of drawing upon third-party data providers to enhance underwriting decisions and marketing strategy. These data providers may operate across industries, with insurance as one of several verticals, or be focused on the insurance industry and its needs.

The need for substantial data sources to supplement and augment internal processes is only growing, driven by the proliferation of predictive analytics, AI, and new consumer expectations for the buying experience. Insurers are also using data to reduce costs—whether for cheaper motor vehicle records or reducing in-person property inspections. Some insurers are also using third-party data for data cleansing or validation.

Applying Third-Party Data

There are three main areas where insurers use third-party data: underwriting, marketing, and claims. Underwriting capabilities like predictive scoring and integrated data and analytics rely on third-party data. Insurers want to be aware of poor risks, and they also want to identify preferred risks. Data pre-fill can speed up the application process, improving customer experience. Data providers may offer geographic data, identity data, personal background information, health records and prescription histories, property characteristics, vehicle characteristics and driver behavior and history, industry classification, property risks data (e.g., earthquakes, floods, wildfires) and/or weather data (current, historical, and predicted).

Insurers use demographic, psychographic, and shopping history data to refine marketing efforts and data pre-fill for distribution. The right data, in combination with analytics and customer segmentation, can help insurers identify prospects and reach out to them at the right time, target marketing approaches better, and identify customers at risk of defection before they let policies lapse or surrender them. With Apple blocking third-party cookies and Google stating it will no longer be using them, insurers have more reason to use third-party data to enhance their information on prospects and clients. Insurers also use distributor data for marketing and recruiting producers.

They leverage external data in product development and predictive scoring for underwriting and fraud, severity, and subrogation/alternative payer for claims.

Claims, or, in the case of some life/annuity lines, payouts, are a major component of most insurers’ expenses. As such, anything insurers can do to settle claims faster (which tends to lead to lower settlements), identify fraud, or avoid or mitigate losses can lead to major cost reductions. Data providers may offer vehicle data (including telematics data), geographic data, identity data, property characteristics, property risks data (e.g., earthquakes, floods, wildfires), social media (individual or commercial), and/or weather data (current, historical, and predicted). Newer data sources include aerial imagery from drones (possibly analyzed using machine learning algorithms), Internet of Things/sensors, social media, and video.

Uses of third-party data for claims include providing a basis for cat models, fraud analytics, identification of potential high-severity claims, more accurate loss estimation, and identifying opportunities for loss avoidance or mitigation. Smaller insurers that may not have a sufficient volume of historical claims data may take advantage of contributory data pools from vendors to obtain enough raw data to develop models.

Data Sources

Few insurers across lines of business continue to rate their ability to leverage third-party data as mature. Third-party data maturity is still relatively rare, though growing—especially in the areas of predictive scoring and integrated data and analytics. Basic capabilities are becoming more widespread, and pilot activity is high.

Insurer interest continues to grow in AI/ML, which require large data sets for training. State and federal regulations, along with GDPR, are an additional driver, as they restrict what data organizations can use and for what purposes. Privacy concerns have made data use transparency critical at the same time. Growing state regulations such as New York State’s cybersecurity regulation and the California Consumer Privacy Act have increased demand for transparency in how organizations use data and for what purposes.

Third-party data providers are consolidating, due to vendors’ desire to maximize wallet share. Data vendors are not always integrated into their acquirers, which can mean challenges for insurers consolidating their data purchases for a more efficient procurement experience. Some core systems providers are going beyond the traditional partnership model and buying data providers outright. Some data providers are partnering with other data providers or AI and analytics firms to enhance the latter firms’ offerings.

Third-party data vendors will become more critical to insurer operations as the importance of third-party data grows. It will become easier for insurers to integrate third-party data as they and vendors build support for APIs and true microservices into their architectures— lowering barriers to adoption and facilitating straight-through processing. Core systems vendors are increasingly incorporating analytics functionality into their offerings, and many already enable web service calls. Key criteria for evaluating data providers include how they validate their data and how often they update data.

See Novarica’s report—Third-Party Data in Insurance: Overview and Prominent Providers—for more insurer third-party data uses cases and profiles of more than 75 data providers that insurers use.

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